Leveraging User-Friendly Network Approaches to Extract Knowledge From High-Throughput Omics Datasets
| Autor(a) principal: | |
|---|---|
| Data de Publicação: | 2019 |
| Outros Autores: | , , , |
| Tipo de documento: | Artigo |
| Idioma: | eng |
| Título da fonte: | Repositório Institucional da FIOCRUZ (ARCA) |
| Texto Completo: | https://www.arca.fiocruz.br/handle/icict/37958 |
Resumo: | Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brazil [Universal 28/2018; grant protocol 427183/2018-9]. LA received a postdoctoral fellowship from the Coordenação de Aperfeiçoamento de Pessoal de 725 Nível Superior (CAPES). AQ acknowledges funding from Fundação Oswaldo Cruz (INOVA - Process VPPIS-001-FIO-18-45). Publication fees were defrayed by Fundação Oswaldo Cruz. The funders had no role in study design, analysis, decision to publish, or preparation of the manuscript |
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Ramos, Pablo Ivan PereiraArge, Luis Willian PachecoLima, Nicholas Costa BarrosoFukutani, Kiyoshi FerreiraQueiroz, Artur Trancoso Lopo de2019-12-16T12:16:34Z2019-12-16T12:16:34Z2019RAMOS, Pablo Ivan Pereira et al. Leveraging user-friendly network approaches to extract knowledge from high-throughput omics datasets. Frontiers in Genetics, v. 10, p. 1-51, 2019.https://www.arca.fiocruz.br/handle/icict/3795810.3389/fgene.2019.01120Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brazil [Universal 28/2018; grant protocol 427183/2018-9]. LA received a postdoctoral fellowship from the Coordenação de Aperfeiçoamento de Pessoal de 725 Nível Superior (CAPES). AQ acknowledges funding from Fundação Oswaldo Cruz (INOVA - Process VPPIS-001-FIO-18-45). Publication fees were defrayed by Fundação Oswaldo Cruz. The funders had no role in study design, analysis, decision to publish, or preparation of the manuscriptFundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Salvador, BA, Brasil / Federal University of Rio de Janeiro. Centro de Ciências da Saúde. Laboratório de Genética Molecular e Biotecnologia Vegetal. Rio de Janeiro, RJ, Brasil.Universidade Federal do Ceará. Departamento de Bioquímica e Biologia Molecular. Fortaleza, CE, Brasil.Fundação José Silveira. Multinational Organization Network Sponsoring Translational and Epidemiological Research. Salvador, BA, Brazil.Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil.Recent technological advances for the acquisition of multi-omics data have allowed an unprecedented understanding of the complex intricacies of biological systems. In parallel, a myriad of computational analysis techniques and bioinformatics tools have been developed, with many efforts directed towards the creation and interpretation of networks from this data. In this review, we begin by examining key network concepts and terminology. Then, computational tools that allow for their construction and analysis from high-throughput omics datasets are presented. We focus on the study of functional relationships such as co-expression, protein-protein interactions, and regulatory interactions that are particularly amenable to modeling using the framework of networks. We envisage that many potential users of these analytical strategies may not be completely literate in programming languages and code adaptation, and for this reason, emphasis is given to tools' user-friendliness, including plugins for the widely adopted Cytoscape software, an open-source, cross-platform tool for network analysis, visualization, and data integration.engFrontiers MediaRedes de correlaçãoGráficoNetwork sequenciamento de alto rendimentoAnálise de redeÔmicasProteína- proteína interaçãoRedes reguladorasBiologia de sistemasCorrelationGraphHigh-throughput sequencingNetwork analysisOmicsProteinproteinRegulatory networksSystems biologyLeveraging User-Friendly Network Approaches to Extract Knowledge From High-Throughput Omics Datasetsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da FIOCRUZ (ARCA)instname:Fundação Oswaldo Cruz (FIOCRUZ)instacron:FIOCRUZLICENSElicense.txtlicense.txttext/plain; charset=utf-82991https://www.arca.fiocruz.br/bitstream/icict/37958/1/license.txt5a560609d32a3863062d77ff32785d58MD51ORIGINALRamos Pablo I . 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| dc.title.pt_BR.fl_str_mv |
Leveraging User-Friendly Network Approaches to Extract Knowledge From High-Throughput Omics Datasets |
| title |
Leveraging User-Friendly Network Approaches to Extract Knowledge From High-Throughput Omics Datasets |
| spellingShingle |
Leveraging User-Friendly Network Approaches to Extract Knowledge From High-Throughput Omics Datasets Ramos, Pablo Ivan Pereira Redes de correlação Gráfico Network sequenciamento de alto rendimento Análise de rede Ômicas Proteína- proteína interação Redes reguladoras Biologia de sistemas Correlation Graph High-throughput sequencing Network analysis Omics Proteinprotein Regulatory networks Systems biology |
| title_short |
Leveraging User-Friendly Network Approaches to Extract Knowledge From High-Throughput Omics Datasets |
| title_full |
Leveraging User-Friendly Network Approaches to Extract Knowledge From High-Throughput Omics Datasets |
| title_fullStr |
Leveraging User-Friendly Network Approaches to Extract Knowledge From High-Throughput Omics Datasets |
| title_full_unstemmed |
Leveraging User-Friendly Network Approaches to Extract Knowledge From High-Throughput Omics Datasets |
| title_sort |
Leveraging User-Friendly Network Approaches to Extract Knowledge From High-Throughput Omics Datasets |
| author |
Ramos, Pablo Ivan Pereira |
| author_facet |
Ramos, Pablo Ivan Pereira Arge, Luis Willian Pacheco Lima, Nicholas Costa Barroso Fukutani, Kiyoshi Ferreira Queiroz, Artur Trancoso Lopo de |
| author_role |
author |
| author2 |
Arge, Luis Willian Pacheco Lima, Nicholas Costa Barroso Fukutani, Kiyoshi Ferreira Queiroz, Artur Trancoso Lopo de |
| author2_role |
author author author author |
| dc.contributor.author.fl_str_mv |
Ramos, Pablo Ivan Pereira Arge, Luis Willian Pacheco Lima, Nicholas Costa Barroso Fukutani, Kiyoshi Ferreira Queiroz, Artur Trancoso Lopo de |
| dc.subject.other.pt_BR.fl_str_mv |
Redes de correlação Gráfico Network sequenciamento de alto rendimento Análise de rede Ômicas Proteína- proteína interação Redes reguladoras Biologia de sistemas |
| topic |
Redes de correlação Gráfico Network sequenciamento de alto rendimento Análise de rede Ômicas Proteína- proteína interação Redes reguladoras Biologia de sistemas Correlation Graph High-throughput sequencing Network analysis Omics Proteinprotein Regulatory networks Systems biology |
| dc.subject.en.pt_BR.fl_str_mv |
Correlation Graph High-throughput sequencing Network analysis Omics Proteinprotein Regulatory networks Systems biology |
| description |
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brazil [Universal 28/2018; grant protocol 427183/2018-9]. LA received a postdoctoral fellowship from the Coordenação de Aperfeiçoamento de Pessoal de 725 Nível Superior (CAPES). AQ acknowledges funding from Fundação Oswaldo Cruz (INOVA - Process VPPIS-001-FIO-18-45). Publication fees were defrayed by Fundação Oswaldo Cruz. The funders had no role in study design, analysis, decision to publish, or preparation of the manuscript |
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2019 |
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2019-12-16T12:16:34Z |
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2019-12-16T12:16:34Z |
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2019 |
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RAMOS, Pablo Ivan Pereira et al. Leveraging user-friendly network approaches to extract knowledge from high-throughput omics datasets. Frontiers in Genetics, v. 10, p. 1-51, 2019. |
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https://www.arca.fiocruz.br/handle/icict/37958 |
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10.3389/fgene.2019.01120 |
| identifier_str_mv |
RAMOS, Pablo Ivan Pereira et al. Leveraging user-friendly network approaches to extract knowledge from high-throughput omics datasets. Frontiers in Genetics, v. 10, p. 1-51, 2019. 10.3389/fgene.2019.01120 |
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